Fish4Knowledge: Collecting and Analyzing Massive Coral Reef Fish Video Data

Herausgegeben:Fisher, Robert B.; Chen-Burger, Yun-Heh; Giordano, Daniela; Hardman, Lynda; Lin, Fang-Pang

• Broschiertes Buch

Produktbeschreibung

This bookgives a start-to-finish overview of the whole Fish4Knowledge project, in 18short chapters, each describing one aspect of the project. The Fish4Knowledgeproject explored the possibilities of big video data, in this case fromundersea video. Recording and analyzing 90 thousand hours of video from tencamera locations, the project gives a 3 year view of fish abundance in severaltropical coral reefs off the coast of Taiwan. The research system built aremote recording network, over 100 Tb of storage, supercomputer processing,video target detection and tracking, fish species recognition and analysis, alarge SQL database to record the results and an efficient retrieval mechanism.Novel user interface mechanisms were developed to provide easy access formarine ecologists, who wanted to explore the dataset. The book is a usefulresource for system builders, as it gives an overview of the many new methodsthat were created to build the Fish4Knowledge system in a manner that alsoallows readers to see how all the components fit together.

Produktdetails

• Intelligent Systems Reference Library 104
• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-80750-8
• Softcover reprint of the original 1st ed. 2016
• Seitenzahl: 340
• Erscheinungstermin: 25. April 2018
• Englisch
• Abmessung: 235mm x 155mm x 19mm
• Gewicht: 530g
• ISBN-13: 9783319807508
• ISBN-10: 3319807501
• Artikelnr.: 53570612

Inhaltsangabe

Overviewof the Fish4Knowledge Project.- User InformationNeeds.- Supercomputing Resources.- Marine Video Data Capture andStorage.- Logical Data Resource Storage.- Software Architecture with Flexibilityfor the Data-Intensive Fish4Knowledge Project.- Fish4Knowledge Database Structure,Creating and Sharing Scientific Data).- Intelligent Workflow Managementfor Fish4Knowledge using the SWELL System.- Fish Detection.- FishTracking.- Hierarchical Classification System with Reject Option for LiveFish Recognition.- Fish Behavior Analysis.- UnderstandingUncertainty Issues in the Exploration of Fish Counts.- Data Groundtruthingand Crowdsourcing.- Counting on Uncertainty: Obtaining Fish Counts from Machine LearningDecisions.- Experiments with the Full Fish4Knowledge Dataset.- TheFish4Knowledge Virtual World Gallery.- Conclusions.